2025 Poster "federated learning" Papers
33 papers found
A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments
Siyuan Wu, Yongzhe Jia, Haolong Xiang et al.
Connecting Federated ADMM to Bayes
Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
Ming Wen, Jiaqi Zhu, Yuedong Xu et al.
DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
Yueyang Yuan, Wenke Huang, Guancheng Wan et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients
Shiyuan Zuo, Xingrun Yan, Rongfei Fan et al.
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models
Rui Ye, Jingyi Chai, Xiangrui Liu et al.
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models
Haokun Chen, Hang Li, Yao Zhang et al.
Federated Continual Instruction Tuning
Haiyang Guo, Fanhu Zeng, Fei Zhu et al.
Federated Domain Generalization with Data-free On-server Matching Gradient
Binh Nguyen, Minh-Duong Nguyen, Jinsun Park et al.
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
Li Zhang, Zhongxuan Han, XiaoHua Feng et al.
FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Chenxin Li et al.
FedRACE: A Hierarchical and Statistical Framework for Robust Federated Learning
Gang Yan, Sikai Yang, Wan Du
FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
Fan Wu, Xinyu Yan, Jiabei Liu et al.
FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling
Hong Huang, Jinhai Yang, Yuan Chen et al.
FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
Pukang Ye, Luo Junwei, Jiachen Shen et al.
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
Seung-Wook Kim, Seongyeol Kim, Jiah Kim et al.
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
Ye Li, Yanchao Zhao, chengcheng zhu et al.
Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
Yehya Farhat, Hamza ElMokhtar Shili, Fangshuo Liao et al.
NoT: Federated Unlearning via Weight Negation
Yasser Khalil, Leo Maxime Brunswic, Soufiane Lamghari et al.
Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model
Ziyuan Yang, Yingyu Chen, Zhiwen Wang et al.
Problem-Parameter-Free Federated Learning
Wenjing Yan, Kai Zhang, Xiaolu Wang et al.
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.
Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
Arian Raje, Baris Askin, Divyansh Jhunjhunwala et al.
Rethinking Fair Federated Learning from Parameter and Client View
Kaiqi Guan, Wenke Huang, Xianda Guo et al.
SparsyFed: Sparse Adaptive Federated Learning
Adriano Guastella, Lorenzo Sani, Alex Iacob et al.
SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
Haoyuan Liang, Shilei Cao, Li et al.
Streaming Federated Learning with Markovian Data
Khiem HUYNH, Malcolm Egan, Giovanni Neglia et al.
Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation
Xinghao Wu, Xuefeng Liu, Jianwei Niu et al.
Towards Federated RLHF with Aggregated Client Preference for LLMs
Feijie Wu, Xiaoze Liu, Haoyu Wang et al.
You Only Communicate Once: One-shot Federated Low-Rank Adaptation of MLLM
Binqian Xu, Haiyang Mei, Zechen Bai et al.